This invention relates generally to software and computer systems, and more specifically, to an advertising system.
Traditionally, advertisers have used geographic location in targeting advertisements in a one-size-fits-all mentality, assuming that users in regions, states, cities, and/or neighborhoods respond to similar types of advertising. For example, users that live in the same zip code as a supermarket may receive advertisements about the supermarket, even if some of those users only shop online for their groceries for organic foods. In this way, the geographic location of those users has been wasted on a supermarket advertisement that is not relevant.
Location-based mobile applications have recently gained popularity among mobile device users. These applications enable users to share their physical locations in real time, providing insight into the daily routines, habits, and favorite places of users of these applications. Although basic demographic information is captured about users of these mobile applications, few advertisers have taken advantage of the location information gathered from these “check-ins,” or location events that include a geographic location in real time.
The proliferation of location-based applications has led to duplicate entries for businesses, inaccurate check-ins, and a lack of mechanisms to handle the uncertainty of user-generated places, such as “Casa de Joe.” Further, advertisers have been struggling to understand how to utilize this new-found location information. Service providers enabling these check-in events only provide the category of location, such as an entertainment venue, restaurant, or park, basic identification information about the place, such as its address and name, and the number of times users have checked into the place. This limited information does not enable advertisers to target users by location. With millions of people sharing their various physical locations at brick and mortar businesses, parks, landmarks, and even public transit vehicles, advertisers have a goldmine of information about users and the locations they visit, yet mechanisms to effectively target users of mobile applications based on their geographic location have not been devised. Tools and methods are needed to aggregate and normalize these locations and evaluate their potential for being paired with an advertisement.